Robust SDE Parameter Estimation Under Missing Time Information Setting

PROBLEM

Framework for SDE parameter estimation without time sequence information, targeting finance and health. However, parameter estimation for SDEs typically relies on accurately timestamped observational sequences.

METHOD

Full abstract

Recent advances in stochastic differential equations (SDEs) have enabled robust modeling of real-world dynamical processes across diverse domains, such as finance, health, and systems biology. However, parameter estimation for SDEs typically relies on accurately timestamped observational sequences. When temporal ordering information is corrupted, missing, or deliberately hidden (e.g., for privacy), existing estimation methods often fail. In this paper, we investigate the conditions under which temporal order can be recovered and introduce a novel framework that simultaneously reconstructs temporal information and estimates SDE parameters. Our approach exploits asymmetries between forward and backward processes, deriving a score-matching criterion to infer the correct temporal order between pairs of observations. We then recover the total order via a sorting procedure and estimate SDE parameters from the reconstructed sequence using maximum likelihood. Finally, we conduct extensive experiments on synthetic and real-world datasets to demonstrate the effectiveness of our method, extending parameter estimation to settings with missing temporal order and broadening applicability in sensitive domains.

RESULT

ScienceToStartup currently rates this 6.0/10 on the public viability pass. Finally, we conduct extensive experiments on synthetic and real-world datasets to demonstrate the effectiveness of our method, extending parameter estimation to settings with missing…

WHY NOW

Financial and Medical Data Processing moved forward this cycle; last verified April 2026. Public score 6.0/10.

Paper Pack

10.48550/arXiv.2601.20268

Robust SDE Parameter Estimation Under Missing Time Information Setting

Framework for SDE parameter estimation without time sequence information, targeting finance and health.

Abstract

Source availability

PDF linked

The paper record includes a public PDF URL.

Extraction status

Parse run linked

A document parse run is attached to this paper.

Proof status

unverified

0 refs; 0 sources; 33% coverage.

What was readable

linkedon file20 anchorsderived fallback22 indexednot indexed

Derived fallback: Estimated from adjacent evidence; not verified from source.

Viability

6.0

Time to MVP

MVP estimate missing

Commercial

No commercial flags on file

Export

Preparing verified analysis

lens / agent

RESULT

PROBLEM

METHOD

WHY NOW

Financial and Medical Data Processing moved forward this cycle; last verified April 2026. Public score 6.0/10.

Claim map

Abstract-backed public claims while anchored extraction refreshes.

Strong 0Mixed 0Weak 4

Evidencepartial
Framework for SDE parameter estimation without time sequence information, targeting finance and health. However, parameter estimation for SDEs typically relies on accurately timestamped observational sequences.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
Recent advances in stochastic differential equations (SDEs) have enabled robust modeling of real-world dynamical processes across diverse domains, such as finance, health, and systems biology. However, parameter estimation for SDEs typically relies on accurately timestamped observational sequences.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
ScienceToStartup currently rates this 6.0/10 on the public viability pass. Finally, we conduct extensive experiments on synthetic and real-world datasets to demonstrate the effectiveness of our method, extending parameter estimation to settings with missing temporal order and broadening applicability in sensitive domains.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
Financial and Medical Data Processing moved forward this cycle; last verified April 2026. Public score 6.0/10.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial

PDF

Preview the source document here, or use the hero PDF action for a new tab.

References(22)

h-Edit: Effective and Flexible Diffusion-Based Editing via Doob’s h-Transform

2025Toàn Nguyên, Kien Do et al.

Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots

2024Vincent Guan, Joseph Janssen et al.

Foundation

Prior WorkLearning Individual Dynamics from Sparse Cross-Sectional Snapshots

6.0

Extension

Builds On ThisPosition: Why a Dynamical Systems Perspective is Needed to Advance Time Series Modeling

2.0

Builds On ThisParallel-in-Time Training of Recurrent Neural Networks for Dynamical Systems Reconstruction

4.0

Owned Distribution

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Robust SDE Parameter Estimation Under Missing Time Information Setting | ScienceToStartup

Paper Pack

10.48550/arXiv.2601.20268

Robust SDE Parameter Estimation Under Missing Time Information Setting

Framework for SDE parameter estimation without time sequence information, targeting finance and health.

Abstract

Source availability

PDF linked

The paper record includes a public PDF URL.

Extraction status

Parse run linked

A document parse run is attached to this paper.

Proof status

unverified

0 refs; 0 sources; 33% coverage.

What was readable

linkedon file20 anchorsderived fallback22 indexednot indexed

Derived fallback: Estimated from adjacent evidence; not verified from source.

Viability

6.0

Time to MVP

MVP estimate missing

Commercial

No commercial flags on file

Export

Preparing verified analysis

lens / agent

RESULT

PROBLEM

METHOD

WHY NOW

Financial and Medical Data Processing moved forward this cycle; last verified April 2026. Public score 6.0/10.

Claim map

Abstract-backed public claims while anchored extraction refreshes.

Strong 0Mixed 0Weak 4

Evidencepartial
Framework for SDE parameter estimation without time sequence information, targeting finance and health. However, parameter estimation for SDEs typically relies on accurately timestamped observational sequences.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
Recent advances in stochastic differential equations (SDEs) have enabled robust modeling of real-world dynamical processes across diverse domains, such as finance, health, and systems biology. However, parameter estimation for SDEs typically relies on accurately timestamped observational sequences.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
ScienceToStartup currently rates this 6.0/10 on the public viability pass. Finally, we conduct extensive experiments on synthetic and real-world datasets to demonstrate the effectiveness of our method, extending parameter estimation to settings with missing temporal order and broadening applicability in sensitive domains.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial
Evidencepartial
Financial and Medical Data Processing moved forward this cycle; last verified April 2026. Public score 6.0/10.
Implicationpartial
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
Verificationpartial
partial

PDF

Preview the source document here, or use the hero PDF action for a new tab.

References(22)

h-Edit: Effective and Flexible Diffusion-Based Editing via Doob’s h-Transform

2025Toàn Nguyên, Kien Do et al.

Identifying Drift, Diffusion, and Causal Structure from Temporal Snapshots

2024Vincent Guan, Joseph Janssen et al.

Foundation

Prior WorkLearning Individual Dynamics from Sparse Cross-Sectional Snapshots

6.0

Extension

Builds On ThisPosition: Why a Dynamical Systems Perspective is Needed to Advance Time Series Modeling

2.0

Builds On ThisParallel-in-Time Training of Recurrent Neural Networks for Dynamical Systems Reconstruction

4.0

Owned Distribution

Subscribe to the weekly brief

Get the weekly shortlist of commercializable papers, benchmark movers, and proof receipts that matter for product execution.

Payload preview

Inspect payload

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Page Freshness

Canonical route, proof status, last verified, refs, sources, and coverage.

Page Freshness

Paper proof surface

Canonical route: /paper/robust-sde-parameter-estimation-under-missing-time-information-setting

stale

Proof freshness: stale
Proof status: unverified
Display score: 6/10
Last proof check: 2026-03-19
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 0
Source count: 0
Coverage: 33%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Endpoint list, payload shape, route context, and copyable handoff data.

Agent Handoff

Robust SDE Parameter Estimation Under Missing Time Information Setting

Canonical ID robust-sde-parameter-estimation-under-missing-time-information-setting | Route /paper/robust-sde-parameter-estimation-under-missing-time-information-setting

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/paper/robust-sde-parameter-estimation-under-missing-time-information-setting

MCP example

{
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}

source_context

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  "topic_slug": null,
  "benchmark_ref": null,
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}

Buildability Receipt

Verdict, compute envelope, blockers, signature state, and receipt links.

Paper proof page receipt window

Watch and verify: Robust SDE Parameter Estimation Under Missing Time Information Setting

/buildability/robust-sde-parameter-estimation-under-missing-time-information-setting

Watchwatch

Subject: Robust SDE Parameter Estimation Under Missing Time Information Setting

Verdict

Watch

Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

Time to first demo

Insufficient data

No first-demo timestamp, owner estimate, or elapsed demo receipt is attached to this surface.

Compute envelope

Structured compute envelope

Insufficient data

Source Proof anchors

Visual citations from the paper document graph.

Source proof

Visual citation anchors from the paper document graph.

20 anchors

proof blockPage 282%

This equation captures one of the core mathematical components of the system. ti = i∆t, where ∆t > 0 is the step size, and T is the number

Page and bbox are available; crop image is pending.

proof blockPage 282%

This equation captures one of the core mathematical components of the system. dimensional standard Wiener process, G ∈Rd×m is a con-

Page and bbox are available; crop image is pending.

proof blockPage 382%

This equation captures one of the core mathematical components of the system. only if J(x) = 0 for all x; in this case, the system satisfies

Page and bbox are available; crop image is pending.

JSON-LD twin

The application/ld+json payload rendered for agents.

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0/3 checks · 0%

References 0 / 33+ references
Sources 0 / 22+ sources
Coverage 33% / 50%50%+ coverage

Build Passport

UNVERIFIED

Build Passport

Build passport pending - Proof Lab budget No verified cost estimate / $7.00 cap

status

missing

reason

passport_row_missing

proof status

unverified

cost/budget

No verified cost estimate

confidence low

next verification path

/api/v1/paper/2601.20268v1/paper-pack
/api/v1/paper/2601.20268v1/build-passport
Generate required assets: Dockerfile.minimal, RUN.sh, EXPECTED_OUTPUT.json, COST_PASSPORT.json

Build artifacts

Brief

missing

Build brief missing until Build Passport data exists.

Source missing: Build Passport payload.

Experiment plan

missing

Experiment plan missing until prototype path is available.

No prototype path attached.

Validation checklist

missing

Validation checklist missing until required assets, cost, and regulatory flags are verified.

No checklist artifact is attached to the Build Passport payload.

Signal Canvas

Derived signals show verified:false until source-backed receipts exist.

Open Signal Canvas

SignalSourceStrengthFreshnessOwner action

Evidence coverage

OpportunityKernel evidence_receipt

0 refs / 0 sources / 33% coverage

stale

Verify missing sources before using this as buyer proof. verified:false

Build readiness

BuildPassport EvidenceState

passport absent

stale

Run Proof Lab or inspect typed missing state. verified:false

Artifact maturity

GitHub and Hugging Face maturity payloads

No public artifact surface observed

stale

Open source artifacts or mark the gap as missing. verified:false

Viability breakdown

decision rows

DimensionCurrent readEvidenceGapsNext test

Technical feasibility

partial

Current read

Runnable path is not fully verified.

Evidence

No Build Passport payload attached.

Gaps

No verified reproduction transcript attached.

Next test

Run minimal reproduction from the Build Passport prototype path.

Market urgency

missing

Current read

Buyer urgency is not verified from source.

Talent buckets

no invented people

Scientific founder

Needed now

No named scientific founder assigned.

Paper authors are not treated as operators without consent.

People

No named person assigned.

Gaps

Founder commitment not verified.

Next verification path

Confirm founder/operator owner.

Translational engineer

Needed now

Prototype owner missing.

Build Passport does not name an implementer.

People

No named person assigned.

ARTIFACTS

No public artifacts yet.

DEFENSIBILITY

Defensibility and confidence evidence pending.

Robust SDE Parameter Estimation Under Missing Time Information Setting

Claim map

PDF

References(22)

Related Papers

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Brief

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Scientific founder

Translational engineer

Timeline

Timeline

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PDF

References(22)

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Constellation map

Competitive landscape

Buzz

Available agents

API/MCP endpoints

Tool contracts

Payload preview

Schema validation

Job trace

Evidence map

Page Freshness

Paper proof surface

Agent Handoff

Robust SDE Parameter Estimation Under Missing Time Information Setting

Buildability Receipt

Watch and verify: Robust SDE Parameter Estimation Under Missing Time Information Setting

Compute envelope

Source Proof anchors

Source proof

JSON-LD twin

Evidence ids

Freshness

Hash state

Signature state

Blockers

Build artifacts

Brief

Experiment plan

Validation checklist

Scientific founder

Translational engineer

Domain operator

GTM lead

Regulatory/clinical advisor